TY - JOUR
T1 - TeleFMG
T2 - A Wearable Force-Myography Device for Natural Teleoperation of Multi-Finger Robotic Hands
AU - Mizrahi, Alon
AU - Sintov, Avishai
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/3/1
Y1 - 2024/3/1
N2 - Teleoperation enables a user to perform dangerous tasks (e.g., work in disaster zones or in chemical plants) from a remote location. Nevertheless, common approaches often provide cumbersome and unnatural usage. In this letter, we propose TeleFMG, an approach for teleoperation of a multi-finger robotic hand through natural motions of the user's hand. By using a low-cost wearable Force-Myography (FMG) device, musculoskeletal activities on the user's forearm are mapped to hand poses which, in turn, are mimicked by a robotic hand. The mapping is performed by a spatio-temporal data-based model based on the Temporal Convolutional Network. The model considers spatial positions of the sensors on the forearm along with temporal dependencies of the FMG signals. A set of experiments show the ability of a teleoperator to control a multi-finger hand through intuitive and natural finger motion. A robot is shown to successfully mimic the user's hand in object grasping and gestures. Furthermore, transfer to a new user is evaluated while showing that fine-tuning with a limited amount of new data significantly improves accuracy.
AB - Teleoperation enables a user to perform dangerous tasks (e.g., work in disaster zones or in chemical plants) from a remote location. Nevertheless, common approaches often provide cumbersome and unnatural usage. In this letter, we propose TeleFMG, an approach for teleoperation of a multi-finger robotic hand through natural motions of the user's hand. By using a low-cost wearable Force-Myography (FMG) device, musculoskeletal activities on the user's forearm are mapped to hand poses which, in turn, are mimicked by a robotic hand. The mapping is performed by a spatio-temporal data-based model based on the Temporal Convolutional Network. The model considers spatial positions of the sensors on the forearm along with temporal dependencies of the FMG signals. A set of experiments show the ability of a teleoperator to control a multi-finger hand through intuitive and natural finger motion. A robot is shown to successfully mimic the user's hand in object grasping and gestures. Furthermore, transfer to a new user is evaluated while showing that fine-tuning with a limited amount of new data significantly improves accuracy.
KW - Telerobotics and teleoperation
KW - multifingered hands
UR - http://www.scopus.com/inward/record.url?scp=85184831516&partnerID=8YFLogxK
U2 - 10.1109/LRA.2024.3362679
DO - 10.1109/LRA.2024.3362679
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AN - SCOPUS:85184831516
SN - 2377-3766
VL - 9
SP - 2933
EP - 2940
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 3
ER -